![]() But caching is difficult because you risk reading data that is not current. It is common to use either Memcached or Redis as external solutions for cachesĪnd other hot data needs, to eliminate the overhead of SQL parsing and transactions. Other limitations: MySQL is saddled with relatively high overhead and cannot deliver optimal speeds. Because it is not designed for very high concurrency, users can experience performance impacts from bottlenecks. ![]() MySQL does not have a strong memory-focused search engine. Large applications, the data cache stored in RAM can grow very large and be subjected to thousands or even millions of requests per second. But the MySQL architecture has limitations when it comes to big data analytics.Ī closer look at the strengths and weaknesses of MySQL reveals five use cases where the RDBMS, powerful though it is, can benefit from the many features of Apache Ignite. MySQL is a widely used open-source relational database management system (RDBMS) and an excellent solution for many applications, including web-scale applications. I compare this output to: du -sch /location/of_Mysql/* | sort -hr | head -n20 ![]() Since my DB is InnoDB, this is just an estimate. WHERE table_schema NOT IN ('mysql','information_schema','performance_schema')
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